It is often desirable to measure a variety of geometric features and performance parameters associated with a tire during both tire manufacturing and testing. Measurement of geometric characteristics of a tire during rotation, including but not limited to parameters such as run-out, mass imbalance, and uniformity measurements, can often be used to help identify potential causes of vehicle vibrations at both high and low traveling speeds. Geometric measurements associated with a tire may also help characterize such phenomena as tread wear and the like over the lifetime of a tire. Additional measurements, such as lateral run-out or sidewall deformation can be used to identify and control such conditions as outward projections or bulges attributable to possible open joints or missing body ply cords within a tire as well as inward facing depressions or dents which may come from a tire joint potentially having too much overlap.
Some conventional measurement methods have employed contact sensors to obtain geometric tire measurements, including but not limited to radial and lateral run-out measurements. For example, sidewall deformation has normally been measured with a contacting sensor along a “clear path” or substantially smooth surface formed along the tire sidewall or shoulder location of a tire. However, off-road tire designs that incorporate tread features along the sidewall and/or shoulder surfaces restrict or eliminate the possible locations for a clear path. Tread features and other structural elements formed along a tire crown inhibit the ability to use contact sensors for obtaining radial measurements. As such, non-contact sensors such as laser sensors and related measurement equipment may be used to obtain the geometric tire measurements. However, a need remains for how best to analyze the obtained measurements to account for the presence of tread features and others in subsequent data processing.
In order to effectively analyze a data set of geometric tire measurements, the obtained measurement data must be free of anomalies. In general, a tire may be modeled geometrically as having substantially uniform tracks along the radial periphery (e.g., tire crown location), lateral periphery (e.g., tire sidewall location), tire shoulder locations and the like. However, data anomalies can be introduced into such a uniform surface model when geometric measurements are obtained relative to certain tire features, such as tread ridges and grooves, tire flashing, and other geometric features that may be formed along the tire crown, shoulder and/or sidewall locations. In addition, data anomalies may be inadvertently introduced into a set of geometric tire measurements because of infrequent errors or overshoot introduced by non-contact measurement equipment.
In light of the need for obtaining clean data sets of tire measurement data to most effectively perform subsequent analysis of tire parameters and related conditions, it is desirable to implement post-measurement processing techniques to improve the quality of geometric tire measurement data. Although known technology for data filtering has been developed, no design has emerged that generally encompasses all of the desired characteristics as hereafter presented in accordance with the subject technology.